Related Experiment Video
Updated: Jul 19, 2025
Author Spotlight: Analysis of Fluorescent-Stained Lipid Droplets with 3D Reconstruction for Hepatic Steatosis Assessment
Published on: June 2, 2023
Non-invasive evaluation of hepatic macrosteatosis in deceased donors
Kayla L Frey1, M Chandler McLeod1, Robert M Cannon1
1University of Alabama at Birmingham, Department of Surgery, Division of Transplantation, Birmingham, AL, USA.
Introduction:
Liver allocation changes have led to increased travel and expenditures, highlighting the need to efficiently identify marginal livers suitable for transplant. We evaluated the validity of existing non-invasive liver quality tests and a novel machine learning-based model at predicting deceased donor macrosteatosis >30%.
Methods:
We compared previously-validated non-invasive tests and a novel machine learning-based model to biopsies in predicting macrosteatosis >30%. We also tested them in populations enriched for macrosteatosis.
Results:
The Hepatic Steatosis Index area-under-the-curve (AUC) was 0.56. At the threshold identified by Youden's J statistic, sensitivity, specificity, positive, and negative predictive values were 49.6%, 58.9%, 14.0%, and 89.7%. Other tests demonstrated comparable results. Machine learning produced the highest AUC (0.71). Even in populations enriched for macrosteatosis, no test was sufficiently predictive.
Conclusion:
Commonly used clinical scoring systems and a novel machine learning-based model were not clinically useful, highlighting the importance of pre-procurement biopsies to facilitate allocation.
